COWLES FOUNDATION FOR RESEARCH IN ECONOMICS
AT YALE UNIVERSITY

Box 208281
New Haven, CT 06520-8281

COWLES FOUNDATION DISCUSSION PAPER NO. 1538

A New Approach to Robust Inference in Cointegration

Sainan Jin
Guanghua School of Management, Peking University
Peter C. B. Phillips
Cowles Foundation, Yale University, University of Auckland & University of York
Yixiao Sun
Department of Economics, University of California, San Diego

October 2005

A new approach to robust testing in cointegrated systems is proposed using nonparametric HAC estimators without truncation. While such HAC estimates are inconsistent, they still produce asymptotically pivotal tests and, as in conventional regression settings, can improve testing and inference. The present contribution makes use of steep origin kernels which are obtained by exponentiating traditional quadratic kernels. Simulations indicate that tests based on these methods have improved size properties relative to conventional tests and better power properties than other tests that use Bartlett or other traditional kernels with no truncation.

JEL Classification: C12; C14; C22

Keywords: Cointegration, HAC estimation, long-run covariance matrix, robust inference, steep origin kernel, fully modified estimation